Multiple Sources of Surprisal Affect Illusory Vowel Epenthesis

Illusory epenthesis is a phenomenon in which listeners report hearing a vowel between a phonotactically illegal consonant cluster, even in the complete absence of vocalic cues. The present study uses Japanese as a test case and investigates the respective roles of three mechanisms that have been claimed to drive the choice of epenthetic vowel—phonetic minimality, phonotactic predictability, and phonological alternations—and propose that they share the same rational goal of searching for the vowel that minimally alters the original speech signal. Additionally, crucial assumptions regarding phonological knowledge held by previous studies are tested in a series of corpus analyses using the Corpus of Spontaneous Japanese. Results show that all three mechanisms can only partially account for epenthesis patterns observed in language users, and the study concludes by discussing possible ways in which the mechanisms might be integrated.

Research on End-to-end Voiceprint Recognition Model Based on Convolutional Neural Network

Speech signal is a time-varying signal, which is greatly affected by individual and environment. In order to improve the end-to-end voice print recognition rate, it is necessary to preprocess the original speech signal to some extent. An end-to-end voiceprint recognition algorithm based on convolutional neural network is proposed. In this algorithm, the convolution and down-sampling of convolutional neural network are used to preprocess the speech signals in end-to-end voiceprint recognition. The one-dimensional and two-dimensional convolution operations were established to extract the characteristic parameters of Meier frequency cepstrum coefficient from the preprocessed signals, and the classical universal background model was used to model the recognition model of voice print. In this study, the principle of end-to-end voiceprint recognition was firstly analyzed, and the process of end-to-end voice print recognition, end-to-end voice print recognition features and Res-FD-CNN network structure were studied. Then the convolutional neural network recognition model was constructed, and the data were preprocessed to form the convolutional layer in frequency domain and the algorithm was tested.

Comparison of Acehnese Pidie Dialect Variations between Acehnese Nagan Raya Dialects of Acehnese People in Peukan Baro District

This research is entitled "Comparison of the Acehnese dialect of the Pidie dialect with the Nagan Raya dialect of Acehnese people in the Peukan Baro district". The formulation of the problem is,How do the variations of the Acehnese dialect of the Pidie dialect compare with the Acehnese dialect of the Nagan Raya in the Acehnese people of Peukan Baro District when interacting using the original speech of the two dialects. This researchaim to describe the comparison of variations in the Acehnese language found in the Acehnese dialect of Pidie with the Acehnese dialect of Nagan Raya, which is used by the Nagan Raya community who live in the Peukan Baro sub-district, when interacting using the native speech of the two regions. The method used in this study is a descriptive method with a qualitative approach. The main data source in this study is the Acehnese speaking community who live in Peukan Baro sub-district. Data was collected by using interview and documentation test techniques. The results of this study indicate that the comparison of language variations based on the usage spoken by the community: (1) comparative data of Acehnese language variations in the form of nouns; (2) comparative data of Acehnese language variations in the form of verbs; (4) comparative data on the variation of the Acehnese language in terms of speech belonging to customs, directions, and kinship calls.

A new speech encryption algorithm based on dual shuffling Hénon chaotic map

Over the past few decades, many algorithms have been proposed to improve the performance of speech encryption over un-secure channel (i.e., Internet). In this paper, the security level was enhanced using a dynamic dual chaotic based on Hénon chaotic map. In the proposed algorithm, the speech elements are shuffled in a random fashion. Moreover, when both Hénon state variables are free to be used for shuffling the index is toggled randomly between them according to toggle bit. After index shuffling each speech element is modified with XOR operation between the original speech element value and the key that is selected randomly from the updated key table. The same chaotic map is used to initiate the empty or full table and provide new table entries from the values that are already shuffled. The experimental results show that the proposed crypto-system is simple, fast with extra random toggling behavior. The high order of substitution make it sensitive to initial condition, common cryptanalysis attacks such as linear and differential attacks are infeasible.

Exposing Speech Transsplicing Forgery with Noise Level Inconsistency

Splicing is one of the most common tampering techniques for speech forgery in many forensic scenarios. Some successful approaches have been presented for detecting speech splicing when the splicing segments have different signal-to-noise ratios (SNRs). However, when the SNRs between the spliced segments are close or even same, no effective detection methods have been reported yet. In this study, noise inconsistency between the original speech and the inserted segment from other speech is utilized to detect the splicing trace. First, noise signal of the suspected speech is extracted by a parameter-optimized noise estimation algorithm. Second, the statistical Mel frequency features are extracted from the estimated noise signal. Finally, the spliced region is located by utilizing a change point detection algorithm on the estimated noise signal. The effectiveness of the proposed method is evaluated on a well-designed speech splicing dataset. The comparative experimental results show that the proposed algorithm can achieve better detection performance than other algorithms.

GMM-Based Evaluation of Synthetic Speech Quality Using 2D Classification in Pleasure-Arousal Scale

The paper focuses on the description of a system for the automatic evaluation of synthetic speech quality based on the Gaussian mixture model (GMM) classifier. The speech material originating from a real speaker is compared with synthesized material to determine similarities or differences between them. The final evaluation order is determined by distances in the Pleasure-Arousal (P-A) space between the original and synthetic speech using different synthesis and/or prosody manipulation methods implemented in the Czech text-to-speech system. The GMM models for continual 2D detection of P-A classes are trained using the sound/speech material from the databases without any relation to the original speech or the synthesized sentences. Preliminary and auxiliary analyses show a substantial influence of the number of mixtures, the number and type of the speech features used the size of the processed speech material, as well as the type of the database used for the creation of the GMMs on the P-A classification process and on the final evaluation result. The main evaluation experiments confirm the functionality of the system developed. The objective evaluation results obtained are principally correlated with the subjective ratings of human evaluators; however, partial differences were indicated, so a subsequent detailed investigation must be performed.

The role of repetitions in Barack Obama’s speech and its Polish translation

The paper presents an analysis of Barack Obama’s first presidential victory speech and its Polish translation. The analysis focuses on loss of repetitions in translation, resulting in modified meaning and effect of the original speech in the target text. Several theoretical vehicles are employed in the paper to explain how those shifts lead to loss in translation and, hence, affect Obama’s message: overt translation, functional equivalence and loss of materiality. The main motivation behind this paper was a desire to investigate ways in which the purpose that political discourse serves in the original language and socio-political context is handled in translation and to what ends.

Lower and Upper Baram Sub-Groups: A Study of Linguistic Affiliation

It is not possible to determine the exact number of indigenous languages of Sarawak, one reason being the dialect-language dichotomy, as some isolects has not been ascertained. Ethnic labels may not reflect a linguistically homogenous group. That is to say that the language varieties spoken by an ethnic group may have a dialectal relationship with one another, or they may be heterogeneous, which means they are mutually unintelligible. This paper reports on the results of a lexicostatistic study that examines linguistic affiliation of a group of languages found along the Tinjar-Baram river basin, namely Berawan, Bakong, Narom, Kiput, Dali,’ and Miriek, and also their links with Kenyah Long Terawan, Lepo’ Tau and Belait in nearby Brunei. The paper also traces their historical past and describes how languages spoken by these ethnolinguistic groups have become affiliated to each other. For some reason or another, e.g. migration in search of greener pastures, internal rivalry or/and conversion to modern religions, these indigenous communities are forced to move away from their original speech communities, and they call themselves by different names in their new localities, usually after the name of a river or a mountain. These factors and categorisation on the basis of similar cultural attributes have caused misinterpretation of the identity of the indigenous groups in the past. The paper will clarify some of the misconceptions regarding the ethnolinguistic groups in the region.

Issues: The Promise of a Speech Act

This essay celebrates the fiftieth anniversary of Research in Phenomenology by reimagining or rethinking the speech act (whether explicit or implicit) that would have launched or inaugurated the journal back in 1971. It does this by rereading Derrida’s signature text on speech act theory, “Signature Event Context,” a text first presented by Derrida in the very year of the journal’s founding. The essay takes Derrida’s theses regarding the speech act’s fundamental relationship to writing, absence, death, and testimony in order to reread some of the first issues of Research in Phenomenology, including the memorial essays contained within them. The essay concludes by suggesting that Research in Phenomenology has done as much as any journal over the last half century to live up to the promise of that original speech act.

SPEECH SIGNAL CRYPTOGRAPHY USING WPT

Digital speech signal is one of the most important types of data used due to the large number of computerized applications that are needed for mankind. Some computerized applications that use digital signals need a high level of security to protect the signal, and to turn it into a vague and incomprehensible signal to any third party, and that is why we have to seek a secure method of cryptography to protect the speech signal. In this research paper we will introduce a method based wavelet packet tree decomposition and reconstruction to generate an encrypted speech, the method will reorder the original speech using a secret number of decomposition levels, the obtained wavelet decomposition sizes will be used to form a speech segments, which must be rearranged in a secret order to get the encrypted speech, the introduced method will be implemented and evaluated to prove the security issues.